[R] Doing partial-f test for stepwise regression

Petr Klasterecky klaster at karlin.mff.cuni.cz
Sun Apr 1 08:49:40 CEST 2007

And what about to read the help page ?anova ...?

When given a sequence of objects, 'anova' tests the models against
      one another in the order specified.

Generally you almost never fit a full model (including all possible 
interactions etc) - no one can interpret such complicated models. Anova 
gives you a comparison between a broader model (the first argument to 
anova) and its submodel(s).


zhuanyi at zay.name napsal(a):
> Hello all,
> I am trying to figure out an optimal linear model by using stepwise
> regression which requires partial f-test, I did some Googling on the
> Internet and realised that someone seemed to ask the question before:
> Jim Milks <jrclmilks at joimail.com> writes: 
>> Dear all: 
>> I have a regression model that has collinearity problems (between 
>> three regressor variables). I need a F-test that will allow me to 
>> compare between full (with all variables) and partial models (minus 
>> 1=< variables). The general F-test formula I'm using is: 
>> F = {[SS(full model) - SS(reduced model)] / (#variables taken out)} / 
>> MSS(full model) 
>> Unfortunately, the ANOVA table parses the SS and MSS between the 
>> variables and does not give the statistics for the regression model as 
>> a whole, otherwise I'd do this by hand. 
>> So, really, I have two questions: 1) Can I just add up all the SS and 
>> MSS for all the variables to get the model SS and MSS and 2) Are 
>> there any functions or packages I can use to calculate the F-statistic? 
>> Just use anova(model1, model2). 
>> (One potential catch: Make sure that both models are fitted to the same
>> data set. Missing values in predictors may interfere.) 
> However, in the answer provided by Mr. Peter Dalgaard,(use
> anova(model1,model2) I could not understand what model1 and model2 are
> supposed to referring to, which one is supposedly to be the full model and
> which one is to be the partial model? Or it does not matter?
> Thanks in advance for help from anyone!
> Regards,
> Anyi Zhu
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Petr Klasterecky
Dept. of Probability and Statistics
Charles University in Prague
Czech Republic

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